Political rhetoric and attitudes toward nationhood: A time-comparative and cross-national analysis of 39 countries
Bibliographic record
Abstract
Research on the relationship between nationhood and individual attitudes prominently focuses on whether – and how – the distinction between ethnic and civic conceptions may be drawn in mass public opinion. We depart from this literature to explain the effects of party rhetoric on shaping more restrictive conceptions of nationhood, which previous research refers to as “ethnic,” “objective,” or “ascriptive” views on nationhood. We do so in three parts: we examine whether political rhetoric, in terms of party manifestos, and individual-level conceptions of nationhood are linked; whether the relationship depends on the ideological alignment between political parties and respondents; and whether political rhetoric and individual predisposition act in combination. We analyze three waves of survey data from the International Social Survey Program’s National Identity module from 1995, 2003 and 2013, covering 58,498 respondents from 39 countries. We find that political rhetoric influences respondents’ conceptions of nationhood. This effect, however, is not as straightforward as initially expected. While the overall political climate does not have a direct effect at the societal level, it does affect the way in which a specific party’s political messages influence the attitudes of their individual recipients. Once the political climate is more ethnocentric, conceptions of nationhood tend to be more restrictive across the board, even among respondents aligned with parties that do not emphasize ethnic conceptions.
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How this classification was reachedexpand
Full frame machine prediction
Teacher imitationNot calibrated prevalence, not ground truth. Human validation pending. The Gemma side is a direct model label for every work in the frame, read from the title-only record. The Codex side is a classifier learned from the 10,348 direct Codex labels and calibrated to design-weighted sample rates; fields without enough sample support carry no Codex call. Candidate is the union of the two sides; consensus is their intersection. These outputs are machine_predicted_unvalidated and are not human labels.
Distilled classifier scores by category (both heads)
| Category | Codex | Gemma |
|---|---|---|
| Metaresearch | 0.002 | 0.003 |
| Meta-epidemiology (narrow) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.000 | 0.000 |
| Bibliometrics | 0.002 | 0.004 |
| Science and technology studies | 0.001 | 0.001 |
| Scholarly communication | 0.001 | 0.001 |
| Open science | 0.000 | 0.002 |
| Research integrity | 0.000 | 0.001 |
| Insufficient payload (model declined to judge) | 0.002 | 0.000 |
Machine scores (provisional)
The two teacher heads of the student model, read on this work. A score orders the frame for review; it never asserts a category, and the validation status ships verbatim with every row.
Baseline scores from an immature model (maturity gate not passed, 7 training rounds). Scores rank; they never assert a category.
score_only:v0-immature-baseline · verbatim from the scoring run: score_only means the number may rank works, and no category label ships from itClassification
machine, unvalidatedMachine predicted; a candidate call from one source (direct Gemma or distilled Codex), not a consensus.
How this classification was reached, model by model and score by score, is at the end of the page under "How this classification was reached".